ML Engineer, Real-Time Rider Pricing & Promotions

Uber; Sunnyvale (CA); On-site; USD 171,000 - 190,000; Full time

Job summary

Uber Marketplace is the core of Uber’s business, shaping rider pricing, discounts, and promotions through advanced ML and data science. You’ll develop algorithms and scalable systems to optimize pricing in real-time and offline settings, driving revenue and rider growth.

You will apply deep learning and AI methods for causal modeling and personalization, collaborating with product and infra teams to evolve pricing platforms and deliver business impact across US locations.

Qualifications

• 3+ years of full-time engineering experience.
• 2+ years of ML experience and building ML models.
• Experience with multiple cross-functional teams (product, science, ops).
• Expertise in one or more OO languages (Python, Go, Java, C++).
• Experience with big-data architecture, ETL frameworks and platforms.
• Solid understanding of latest ML technologies and libraries.
• Fast learner with willingness to step out of comfort zone.

Responsibilities

• Develop and implement ML and optimization solutions for rider pricing, discounts, and targeting.
• Build and scale models and systems for real-time and offline promotions and pricing.
• Collaborate with cross-functional teams to drive measurable business outcomes.
• Set technical directions for ML, serving, and optimization components impacting Uber's growth.

Skills

ML experience

Big data architectures

Cross-functional collaboration

Programming languages

ETL frameworks

Fast learner

Education

Bachelor's degree in CS/Engineering/Math or related field

Tools

Spark

ETL tools

Big data platforms

Job description

Uber Marketplace is the core of Uber’s business, shaping rider pricing, discounts, and promotions through advanced ML and data science. You’ll develop algorithms and scalable systems to optimize pricing in real-time and offline settings, driving revenue and rider growth.

You will apply deep learning and AI methods for causal modeling and personalization, collaborating with product and infra teams to evolve pricing platforms and deliver business impact across US locations.